Is my model over-fitted or underfitted?

Hi all, I am new to xgboost and I am using it to learn two variables (a and b) using a 10 x 10 million data set. The parameters that I am using are

params = {‘tree_method’: ‘gpu_hist’,

and i train with 100 rounds.

Basically, the reconstruction looks like it didn’t pick up the signal. Y axis is the reconstructed a. X axis is the truth. the red line is just a diagonal.


My conclusion would be that the classifier is not complex enough. However, when i increase the max_depth the model performs much worse, or even go to the degree where i stop having any sensitivity at all.

Can anyone give me a hint on what to do?

and reconstructed b


(since I can only post one picture at a time)